Description Usage Arguments Details See Also Examples

Prepare the measurement recipe

1 2 3 |

`values.load` |
matrix of starting or fixed values for factor loadings. For models with regime-specific factor loadings provide a list of matrices of factor loadings. |

`params.load` |
matrix or list of matrices. Contains parameter names of the factor loadings. |

`values.exo` |
matrix or list of matrices. Contains starting/fixed values of the covariate regression slopes. |

`params.exo` |
matrix or list of matrices. Parameter names of the covariate regression slopes. |

`values.int` |
vector of intercept values specified as matrix or list of matrices. Contains starting/fixed values of the intercepts. |

`params.int` |
vector of names for intercept parameters specified as a matrix or list of matrices. |

`obs.names` |
vector of names for the observed variables in the order they appear in the measurement model. |

`state.names` |
vector of names for the latent variables in the order they appear in the measurement model. |

`exo.names` |
(optional) vector of names for the exogenous variables in the order they appear in the measurement model. |

The values.* arguments give the starting and fixed values for their respective matrices. The params.* arguments give the free parameter labels for their respective matrices. Numbers can be used as labels. The number 0 and the character 'fixed' are reserved for fixed parameters.

When a single matrix is given to values.*, that matrix is not regime-switching. Correspondingly, when a list of length r is given, that matrix is regime-switching with values and params for the r regimes in the elements of the list.

Methods that can be used include: `print`

, `printex`

, `show`

1 2 3 4 5 6 7 8 | ```
prep.measurement(diag(1, 5), diag("lambda", 5))
prep.measurement(matrix(1, 5, 5), diag(paste0("lambda_", 1:5)))
prep.measurement(diag(1, 5), diag(0, 5)) #identity measurement model
#Regime-switching measurement model where the first latent variable is
# active for regime 1, and the second latent variable is active for regime 2
# No free parameters are present.
prep.measurement(values.load=list(matrix(c(1,0), 1, 2), matrix(c(0, 1), 1, 2)))
``` |

dynr documentation built on Feb. 9, 2018, 6:07 a.m.

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